A single transcript for the prognosis of disease severity in COVID-19 patients

Disease progression associated cytokines in COVID-19 patients with deteriorating and recovering health conditions

Understanding the immune response to COVID-19 is challenging due to its high variability among individuals. To identify differentially expressed cytokines between the deteriorating and recovering phases, we analyzed the Electronic Health Records (EHR) and cytokine profile data in a COVID-19 cohort of 444 infected patients and 145 non-infected healthy individuals. We categorized each patient's progression into Deterioration Phase (DP) and Recovery Phase (RP) using longitudinal neutrophil, lymphocyte and lactate dehydrogenase levels. A random forest model was built using healthy and severe patients to compute the contribution of each cytokine toward disease progression using Shapley Additive Explanations (SHAP). SHAP values were used for supervised clustering to identify DP and RP-related samples and their associated cytokines. The identified clusters effectively discriminated DP and RP samples, suggesting that the cytokine profiles differed between deteriorating and recovering health conditions. Especially, CXCL10, GDF15, PTX3, and TNFSF10 were differentially expressed between the DP and RP samples, which are involved in the JAK-STAT, NF- κ B, and MAPK signaling pathways contributing to the inflammatory response. Collectively, we characterized the immune response in terms of disease progression of COVID-19 with deteriorating and recovering health conditions.

High Serum S100A12 as a Diagnostic and Prognostic Biomarker for Severity, Multidrug-Resistant Bacteria Superinfection and Herpes Simplex Virus Reactivation in COVID-19

Neutrophils are critical immune cells in severe coronavirus disease 2019 (COVID-19). S100 calcium-binding protein A12 (S100A12) is highly expressed in neutrophils during acute inflammation. The aim of this study was to evaluate serum S100A12 levels as a diagnostic and prognostic tool in COVID-19. Serum samples of patients with moderate and severe COVID-19 were collected during 2020 to 2024. Enzyme-linked immunosorbent assay was used to measure serum S100A12 levels in 63 patients with moderate COVID-19, 60 patients with severe disease and 33 healthy controls. Serum S100A12 levels were elevated in moderate COVID-19 compared to controls and were even higher in severe cases. In moderate disease, serum S100A12 levels positively correlated with immune cell counts. While C-reactive protein and procalcitonin are established inflammation markers, they did not correlate with serum S100A12 levels in either patient cohort. Patients with severe COVID-19 and vancomycin-resistant enterococcus (VRE) infection had increased S100A12 levels. Elevated S100A12 levels were also observed in patients with herpes simplex reactivation. Fungal superinfections did not alter S100A12 levels. These data show that serum S100A12 increases in moderate and severe COVID-19 and is further elevated by VRE bloodstream infection and herpes simplex reactivation. Therefore, S100A12 may serve as a novel biomarker for severe COVID-19 and an early diagnostic indicator for bacterial and viral infections.

ISMI-VAE: A deep learning model for classifying disease cells using gene expression and SNV data

Various studies have linked several diseases, including cancer and COVID-19, to single nucleotide variations (SNV). Although single-cell RNA sequencing (scRNA-seq) technology can provide SNV and gene expression data, few studies have integrated and analyzed these multimodal data. To address this issue, we introduce Interpretable Single-cell Multimodal Data Integration Based on Variational Autoencoder (ISMI-VAE). ISMI-VAE leverages latent variable models that utilize the characteristics of SNV and gene expression data to overcome high noise levels and uses deep learning techniques to integrate multimodal information, map them to a low-dimensional space, and classify disease cells. Moreover, ISMI-VAE introduces an attention mechanism to reflect feature importance and analyze genetic features that could potentially cause disease. Experimental results on three cancer data sets and one COVID-19 data set demonstrate that ISMI-VAE surpasses the baseline method in terms of both effectiveness and interpretability and can effectively identify disease-causing gene features.

Quantitative and Longitudinal Assessment of Systemic Innate Immunity in Health and Disease Using a 2D Gene Model

Dysregulation of innate immunity is deeply involved in infectious and autoimmune diseases. For a better understanding of pathogenesis and improved management of these diseases, it is of vital importance to implement convenient monitoring of systemic innate immunity. Built upon our previous works on the host transcriptional response to infection in peripheral blood, we proposed a 2D gene model for the simultaneous assessment of two major components of systemic innate immunity, including VirSig as the signature of the host response to viral infection and BacSig as the signature of the host response to bacterial infection. The revelation of dysregulation in innate immunity by this 2D gene model was demonstrated with a wide variety of transcriptome datasets. In acute infection, distinctive patterns of VirSig and BacSig activation were observed in viral and bacterial infection. In comparison, both signatures were restricted to a defined range in the vast majority of healthy adults, regardless of age. In addition, BacSig showed significant elevation during pregnancy and an upward trend during development. In tuberculosis (TB), elevation of BacSig and VirSig was observed in a significant portion of active TB patients, and abnormal BacSig was also associated with a longer treatment course. In cystic fibrosis (CF), abnormal BacSig was observed in a subset of patients, and no overall change in BacSig abnormality was observed after the drug treatment. In systemic sclerosis-associated interstitial lung disease (SSc-ILD), significant elevation of VirSig and BacSig was observed in some patients, and treatment with a drug led to the further deviation of BacSig from the control level. In systemic lupus erythematosus (SLE), positivity for the anti-Ro autoantibody was associated with significant elevation of VirSig in SLE patients, and the additive effect of VirSig/BacSig activation was also observed in SLE patients during pregnancy. Overall, these data demonstrated that the 2D gene model can be used to assess systemic innate immunity in health and disease, with the potential clinical applications including patient stratification, prescription of antibiotics, understanding of pathogenesis, and longitudinal monitoring of treatment response.

The malarial blood transcriptome: translational applications

The blood transcriptome of malaria patients has been used extensively to elucidate the pathophysiological mechanisms and host immune responses to disease, identify candidate diagnostic and prognostic biomarkers, and reveal new therapeutic targets for drug discovery. This review gives a high-level overview of the three main translational applications of these studies (diagnostics, prognostics, and therapeutics) by summarising recent literature and outlining the main limitations and future directions of each application. It highlights the need for consistent and accurate definitions of disease states and subject groups and discusses how prognostic studies must distinguish clearly between analyses that attempt to predict future disease states and those which attempt to discriminate between current disease states (classification). Lastly it examines how many promising therapeutics fail due to the choice of imperfect animal models for pre-clinical testing and lack of appropriate validation studies in humans, and how future transcriptional studies may be utilised to overcome some of these limitations.

Immune Characteristic Genes and Neutrophil Immune Transformation Studies in Severe COVID-19

As a disease causing a global pandemic, the progression of symptoms to severe disease in patients with COVID-19 often has adverse outcomes, but research on the immunopathology of COVID-19 severe disease remains limited. In this study, we used mRNA-seq data from the peripheral blood of COVID-19 patients to identify six COVID-19 severe immune characteristic genes (FPR1, FCGR2A, TLR4, S100A12, CXCL1, and L TF), and found neutrophils to be the critical immune cells in COVID-19 severe disease. Subsequently, using scRNA-seq data from bronchoalveolar lavage fluid from COVID-19 patients, neutrophil subtypes highly expressing the S100A family were found to be located at the end of cellular differentiation and tended to release neutrophil extracellular traps. Finally, it was also found that alveolar macrophages, macrophages, and monocytes with a high expression of COVID-19 severe disease immune characteristic genes may influence neutrophils through intercellular ligand-receptor pairs to promote neutrophil extracellular trap release. This study provides immune characteristic genes, critical immune pathways, and immune cells in COVID-19 severe disease, explores intracellular immune transitions of critical immune cells and pit-induced intercellular communication of immune transitions, and provides new biomarkers and potential drug targets for the treatment of patients with COVID-19 severe disease.

Hypoxia and Activation of Neutrophil Degranulation-Related Genes in the Peripheral Blood of COVID-19 Patients

Severe COVID-19 is characterized by systematic hyper-inflammation and subsequent damage to various organs. Therefore, it is critical to trace this cascade of hyper-inflammation. Blood transcriptome has been routinely utilized in the interrogation of host immune response in COVID-19 and other infectious conditions. In this study, consensus gene dysregulation in the blood was obtained from 13 independent transcriptome studies on COVID-19. Among the up-regulated genes, the most prominent functional categories were neutrophil degranulation and cell cycle, which is clearly different from the classical activation of interferon signaling pathway in seasonal flu. As for the potential upstream causal factors of the atypical gene dysregulation, systemic hypoxia was further examined because it is much more widely reported in COVID-19 than that in seasonal flu. It was found that both physiological and pathological hypoxia can induce activation of neutrophil degranulation-related genes in the blood. Furthermore, COVID-19 patients with different requirement for oxygen intervention showed distinctive levels of gene expression related to neutrophil degranulation in the whole blood, which was validated in isolated neutrophils. Thus, activation of neutrophil degranulation-related genes in the blood of COVID-19 could be partially attributed to hypoxia. Interestingly, similar pattern was also observed in H1N1 infection (the cause of Spanish flu) and several other severe respiratory viral infections. As for the molecular mechanism, both HIF-dependent and HIF-independent pathways have been examined. Since the activation of neutrophil degranulation-related genes is highly correlated with disease severity in COVID-19, early detection of hypoxia and active intervention may prevent further activation of neutrophil degranulation-related genes and other harmful downstream hyper-inflammation. This common mechanism is applicable to current and future pandemic as well as the severe form of common respiratory infection.

Circulating markers of extracellular matrix remodelling in severe COVID-19 patients

BACKGROUND

Abnormal remodelling of the extracellular matrix (ECM) has generally been linked to pulmonary inflammation and fibrosis and may also play a role in the pathogenesis of severe COVID-19. To further elucidate the role of ECM remodelling and excessive fibrogenesis in severe COVID-19, we examined circulating levels of mediators involved in various aspects of these processes in COVID-19 patients.

METHODS

Serial blood samples were obtained from two cohorts of hospitalised COVID-19 patients (n = 414). Circulating levels of ECM remodelling mediators were quantified by enzyme immunoassays in samples collected during hospitalisation and at 3-month follow-up. Samples were related to disease severity (respiratory failure and/or treatment at the intensive care unit), 60-day total mortality and pulmonary pathology after 3-months. We also evaluated the direct effect of inactivated SARS-CoV-2 on the release of the different ECM mediators in relevant cell lines.

RESULTS

Several of the measured markers were associated with adverse outcomes, notably osteopontin (OPN), S100 calcium-binding protein A12 and YKL-40 were associated with disease severity and mortality. High levels of ECM mediators during hospitalisation were associated with computed tomography thorax pathology after 3-months. Some markers (i.e. growth differential factor 15, galectin 3 and matrix metalloproteinase 9) were released from various relevant cell lines (i.e. macrophages and lung cell lines) in vitro after exposure to inactivated SARS-CoV-2 suggesting a direct link between these mediators and the causal agent of COVID-19.

CONCLUSION

Our findings highlight changes to ECM remodelling and particularly a possible role of OPN, S100A12 and YKL-40 in the pathogenesis of severe COVID-19.

Multi-omic profiling reveals early immunological indicators for identifying COVID-19 Progressors

We sought to better understand the immune response during the immediate post-diagnosis phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by identifying molecular associations with longitudinal disease outcomes. Multi-omic analyses identified differences in immune cell composition, cytokine levels, and cell subset-specific transcriptomic and epigenomic signatures between individuals on a more serious disease trajectory (Progressors) as compared to those on a milder course (Non-progressors). Higher levels of multiple cytokines were observed in Progressors, with IL-6 showing the largest difference. Blood monocyte cell subsets were also skewed, showing a comparative decrease in non-classical CD14-CD16+ and intermediate CD14+CD16+ monocytes. In lymphocytes, the CD8+ T effector memory cells displayed a gene expression signature consistent with stronger T cell activation in Progressors. These early stage observations could serve as the basis for the development of prognostic biomarkers of disease risk and interventional strategies to improve the management of severe COVID-19. BACKGROUND: Much of the literature on immune response post-SARS-CoV-2 infection has been in the acute and post-acute phases of infection. TRANSLATIONAL SIGNIFICANCE: We found differences at early time points of infection in approximately 160 participants. We compared multi-omic signatures in immune cells between individuals progressing to needing more significant medical intervention and non-progressors. We observed widespread evidence of a state of increased inflammation associated with progression, supported by a range of epigenomic, transcriptomic, and proteomic signatures. The signatures we identified support other findings at later time points and serve as the basis for prognostic biomarker development or to inform interventional strategies.

A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling

Altered myeloid inflammation and lymphopenia are hallmarks of severe infections. We identified the upregulated EN-RAGE gene program in airway and blood myeloid cells from patients with acute lung injury from SARS-CoV-2 or other causes across 7 cohorts. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGEhi myeloid cells express features consistent with suppressor cell functionality, including low HLA-DR and high PD-L1. Sustained EN-RAGE program expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers. IL-6 upregulated many EN-RAGE program genes in monocytes in vitro. IL-6 signaling blockade by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of EN-RAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

A two-gene marker for the two-tiered innate immune response in COVID-19 patients

For coronavirus disease 2019 (COVID-19), a pandemic disease characterized by strong immune dysregulation in severe patients, convenient and efficient monitoring of the host immune response is critical. Human hosts respond to viral and bacterial infections in different ways, the former is characterized by the activation of interferon stimulated genes (ISGs) such as IFI27, while the latter is characterized by the activation of anti-bacterial associated genes (ABGs) such as S100A12. This two-tiered innate immune response has not been examined in COVID-19. In this study, the activation patterns of this two-tiered innate immune response represented by IFI27 and S100A12 were explored based on 1421 samples from 17 transcriptome datasets derived from the blood of COVID-19 patients and relevant controls. It was found that IFI27 activation occurred in most of the symptomatic patients and displayed no correlation with disease severity, while S100A12 activation was more restricted to patients under severe and critical conditions with a stepwise activation pattern. In addition, most of the S100A12 activation was accompanied by IFI27 activation. Furthermore, the activation of IFI27 was most pronounced within the first week of symptom onset, but generally waned after 2-3 weeks. On the other hand, the activation of S100A12 displayed no apparent correlation with disease duration and could last for several months in certain patients. These features of the two-tiered innate immune response can further our understanding on the disease mechanism of COVID-19 and may have implications to the clinical triage. Development of a convenient two-gene protocol for the routine serial monitoring of this two-tiered immune response will be a valuable addition to the existing laboratory tests.

Host biomarker-based quantitative rapid tests for detection and treatment monitoring of tuberculosis and COVID-19

Diagnostic services for tuberculosis (TB) are not sufficiently accessible in low-resource settings, where most cases occur, which was aggravated by the COVID-19 pandemic. Early diagnosis of pulmonary TB can reduce transmission. Current TB-diagnostics rely on detection of Mycobacterium tuberculosis (Mtb) in sputum requiring costly, time-consuming methods, and trained staff. In this study, quantitative lateral flow (LF) assays were used to measure levels of seven host proteins in sera from pre-COVID-19 TB patients diagnosed in Europe and latently Mtb-infected individuals (LTBI), and from COVID-19 patients and healthy controls. Analysis of host proteins showed significantly lower levels in LTBI versus TB (AUC:0 · 94) and discriminated healthy individuals from COVID-19 patients (0 · 99) and severe COVID-19 from TB. Importantly, these host proteins allowed treatment monitoring of both respiratory diseases. This study demonstrates the potential of non-sputum LF assays as adjunct diagnostics and treatment monitoring for COVID-19 and TB based on quantitative detection of multiple host biomarkers.

Significance of Immune Status of SARS-CoV-2 Infected Patients in Determining the Efficacy of Therapeutic Interventions

Coronavirus disease 2019 (COVID-19) is now being investigated for its distinctive patterns in the course of disease development which can be indicated with miscellaneous immune responses in infected individuals. Besides this series of investigations on the pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), significant fundamental immunological and physiological processes are indispensable to address clinical markers of COVID-19 disease and essential to identify or design effective therapeutics. Recent developments in the literature suggest that deficiency of type I interferon (IFN) in serum samples can be used to represent a severe progression of COVID-19 disease and can be used as the basis to develop combined immunotherapeutic strategies. Precise control over inflammatory response is a significant aspect of targeting viral infections. This account presents a brief review of the pathophysiological characteristics of the SARS-CoV-2 virus and the understanding of the immune status of infected patients. We further discuss the immune system’s interaction with the SARS-CoV-2 virus and their subsequent involvement of dysfunctional immune responses during the progression of the disease. Finally, we highlight some of the implications of the different approaches applicable in developing promising therapeutic interventions that redirect immunoregulation and viral infection.